fix_metadata.rmd

Load libraries

library(tidyverse)
library(lubridate)

metadata <- read_csv("../data/metadata.csv")

Parsed with column specification:
cols(
  .default = col_double(),
  DATE = col_character(),
  WDW_TICKET_SEASON = col_logical(),
  SEASON = col_character(),
  HOLIDAYN = col_character(),
  WDWTICKETSEASON = col_logical(),
  WDWRaceN = col_character(),
  WDWeventN = col_character(),
  WDWSEASON = col_character(),
  MKeventN = col_character(),
  EPeventN = col_character(),
  HSeventN = col_logical(),
  AKeventN = col_logical(),
  HOLIDAYJ = col_character(),
  inSession = col_character(),
  inSession_Enrollment = col_character(),
  inSession_wdw = col_character(),
  inSession_dlr = col_character(),
  inSession_sqrt_WDW = col_character(),
  inSession_sqrt_DLR = col_character(),
  inSession_California = col_character()
  # ... with 77 more columns
)
See spec(...) for full column specifications.
13258 parsing failures.
row         col   expected   actual                   file
  1 MKCLOSE     valid date 24:00:00 '../data/metadata.csv'
  1 MKEMHCLOSE  valid date 27:00:00 '../data/metadata.csv'
  1 MKCLOSEYEST valid date 26:00:00 '../data/metadata.csv'
  1 MKCLOSETOM  valid date 24:00:00 '../data/metadata.csv'
  1 EPCLOSEYEST valid date 25:00:00 '../data/metadata.csv'
... ........... .......... ........ ......................
See problems(...) for more details.

metadata

<<<<<<< HEAD <<<<<<< HEAD <<<<<<< HEAD ======= >>>>>>> aea5e10bf472d59f9c83b00d454098e46b34fa18 ======= >>>>>>> 5fd5edc7dfc94899454e26c50ac66ebad7ae835a ======= >>>>>>> a6c8c0cfdbf3114f85aae4906de541e3974731b5

mk_metadata <- metadata %>%
  select(DATE, SEASON, HOLIDAYPX, HOLIDAYN, WDWMAXTEMP, WDWMINTEMP, WDWMEANTEMP, HOLIDAYJ, MKOPEN, MKCLOSE, MKEMHOPEN, MKEMHCLOSE, WEATHER_WDWPRECIP,
         MKPRDDT1, MKPRDDT2, MKPRDNT1, MKPRDNT2, MKFIRET1, MKFIRET2)
ep_metadata <- metadata %>%
  select(DATE, SEASON, HOLIDAYPX, HOLIDAYN, WDWMAXTEMP, WDWMINTEMP, WDWMEANTEMP, HOLIDAYJ, EPOPEN, EPCLOSE, EPEMHOPEN, EPEMHCLOSE, WEATHER_WDWPRECIP,
         EPFIRET1, EPFIRET2)
hs_metadata <- metadata %>%
  select(DATE, SEASON, HOLIDAYPX, HOLIDAYN, WDWMAXTEMP, WDWMINTEMP, WDWMEANTEMP, HOLIDAYJ, HSOPEN, HSCLOSE, HSEMHOPEN, HSEMHCLOSE, WEATHER_WDWPRECIP,
         HSPRDDT1, HSFIRET1, HSFIRET2, HSSHWNT1, HSSHWNT2)
ak_metadata <- metadata %>%
  select(DATE, SEASON, HOLIDAYPX, HOLIDAYN, WDWMAXTEMP, WDWMINTEMP, WDWMEANTEMP, HOLIDAYJ, AKOPEN, AKCLOSE, AKEMHOPEN, AKEMHCLOSE, WEATHER_WDWPRECIP,
         AKPRDDT1, AKPRDDT2, AKSHWNT1, AKSHWNT2)

<<<<<<< HEAD

metadata$DATE <- format(as.POSIXct(mdy(metadata$DATE) + 1, format = '%m/%d/%Y %H:%M:%S'), format='%Y-%m-%d')
head(metadata)

=======

metadata$DATE <- format(as.POSIXct(mdy(metadata$DATE) + 1, format = '%m/%d/%Y %H:%M:%S'), format='%m/%d/%Y')
head(metadata)

<<<<<<< HEAD <<<<<<< HEAD >>>>>>> aea5e10bf472d59f9c83b00d454098e46b34fa18 ======= >>>>>>> 5fd5edc7dfc94899454e26c50ac66ebad7ae835a ======= >>>>>>> a6c8c0cfdbf3114f85aae4906de541e3974731b5

wdw_metadata <- metadata %>%
  select(DATE, SEASON, HOLIDAYPX, HOLIDAYN, WDWMAXTEMP, WDWMINTEMP, WDWMEANTEMP, HOLIDAYJ, WEATHER_WDWPRECIP)
mk_metadata <- metadata %>%
  select(DATE, MKOPEN, MKCLOSE, MKEMHOPEN, MKEMHCLOSE, MKPRDDT1, MKPRDDT2, MKPRDNT1, MKPRDNT2, MKFIRET1, MKFIRET2)
ep_metadata <- metadata %>%
  select(DATE, EPOPEN, EPCLOSE, EPEMHOPEN, EPEMHCLOSE, EPFIRET1, EPFIRET2)
hs_metadata <- metadata %>%
  select(DATE, HSOPEN, HSCLOSE, HSEMHOPEN, HSEMHCLOSE, HSPRDDT1, HSFIRET1, HSFIRET2, HSSHWNT1, HSSHWNT2)
ak_metadata <- metadata %>%
  select(DATE, AKOPEN, AKCLOSE, AKEMHOPEN, AKEMHCLOSE, AKPRDDT1, AKPRDDT2, AKSHWNT1, AKSHWNT2)

head(wdw_metadata)

<<<<<<< HEAD <<<<<<< HEAD <<<<<<< HEAD ======= >>>>>>> aea5e10bf472d59f9c83b00d454098e46b34fa18 ======= >>>>>>> 5fd5edc7dfc94899454e26c50ac66ebad7ae835a ======= >>>>>>> a6c8c0cfdbf3114f85aae4906de541e3974731b5

head(mk_metadata)

<<<<<<< HEAD <<<<<<< HEAD <<<<<<< HEAD ======= >>>>>>> aea5e10bf472d59f9c83b00d454098e46b34fa18 ======= >>>>>>> 5fd5edc7dfc94899454e26c50ac66ebad7ae835a ======= >>>>>>> a6c8c0cfdbf3114f85aae4906de541e3974731b5

xhot_days <- wdw_metadata %>%
  select(DATE, WDWMEANTEMP) %>%
  filter(WDWMEANTEMP >= 85)

hot_days <- wdw_metadata %>%
  select(DATE, WDWMEANTEMP) %>%
  filter(WDWMEANTEMP < 85 & WDWMEANTEMP >= 79.8)

normal_days <- wdw_metadata %>%
  select(DATE, WDWMEANTEMP) %>%
  filter(WDWMEANTEMP >= 71.3 & WDWMEANTEMP < 79.8)

cool_days <- wdw_metadata %>%
  select(DATE, WDWMEANTEMP) %>%
  filter(WDWMEANTEMP >= 62.8 & WDWMEANTEMP < 71.3)

xcool_days <- wdw_metadata %>%
  select(DATE, WDWMEANTEMP) %>%
  filter(WDWMEANTEMP < 62.8)

xcool_days

<<<<<<< HEAD <<<<<<< HEAD <<<<<<< HEAD ======= >>>>>>> aea5e10bf472d59f9c83b00d454098e46b34fa18 ======= >>>>>>> 5fd5edc7dfc94899454e26c50ac66ebad7ae835a ======= >>>>>>> a6c8c0cfdbf3114f85aae4906de541e3974731b5